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Possible Advantages of Conceptual Framework

The expected outcomes of the study are as follows:

• Efficient Framework: The proposed study introduces a completely novel framework that can effectively perform knowledge discovery from Big Data considering cloud environment.

  • • Cost Effective Knowledge Discovery: It is anticipated that the study will put forward an application that considers real time dataset and is compliant of time and space complexity.
  • • Superlative Semantics: The proposed system attempts to make use enriched ontological representation in the object properties in the context of cloud SaaS service discovery on big data.
  • • Computational Effective Data Mining: The proposed system performs modelling of the big data based on dependent and independent constraint, where in all the study phases, the proposed system performs filtering of irrelevant contextual based data that reduces computational complexity.

Research Implication

The proposed system offers customizable analytical features on educational data using BigData approach that offers a highly enriched knowledge delivery process in any forms of educational system. The technical feasibility of the proposed system is quite cost effective owing to adoption of open-source tools e.g. Hadoop and MapReduce software framework. The economic feasibility of the conceptual framework is also quite high as hardware / infrastructure dependency becomes negligible owing to adoption of cloud services. Usage of novel semantics along with data mining algorithms allows the conceptual framework to extract maximum knowledge from the highly challenging unstructured data. The implication of the proposed research work is quite high and is not restricted to a specific case study. It can be applied on school-level educational system to advanced-level educational system on any discipline. Owing to the adoption of open source framework, it can take the input of high-dimensional data that can be either semi-structure or unstructured.

 
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